180 citations · 1.1k across the 26 of their papers we have counts for
3 papers · 1 filter
Building Population-Informed Priors for Bayesian Inference Using Data-Consistent Stochastic Inversion
Rebekah D. White, John D. Jakeman, Tim Wildey +1
Bayesian inference provides a powerful tool for leveraging observational data to inform model predictions and uncertainties. However, when such data is limited, Bayesian inference…
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
Matthew Lowery, John Turnage, Zachary Morrow +4
This paper introduces the Kernel Neural Operator (KNO), a provably convergent operator-learning architecture that utilizes compositions of deep kernel-based integral operators for…
Grouped approximate control variate estimators
Alex A. Gorodetsky, John D. Jakeman, Michael S. Eldred
This paper analyzes the approximate control variate (ACV) approach to multifidelity uncertainty quantification in the case where weighted estimators are combined to form the compon…